Better fix training

assets/i18n/languages/en_US.json

@@ -17,6 +17,10 @@
     "Model Name": "Model Name",
     "Enter model name": "Enter model name",
     "Dataset Path": "Dataset Path",
+    "Dataset Creator": "Dataset Creator",
+    "Dataset Name": "Dataset Name",
+    "Enter dataset name": "Enter dataset name",
+    "Upload Audio Dataset": "Upload Audio Dataset",
     "The audio file has been successfully added to the dataset. Please click the preprocess button.": "The audio file has been successfully added to the dataset. Please click the preprocess button.",
     "Enter dataset path": "Enter dataset path",
     "Sampling Rate": "Sampling Rate",

assets/i18n/languages/es_ES.json

@@ -15,6 +15,10 @@
   "Model Name": "Nombre del modelo",
   "Enter model name": "Introduzca el nombre del modelo",
   "Dataset Path": "Ruta del dataset",
+  "Dataset Creator": "Creador de datasets",
+  "Dataset Name": "Nombre del dataset",
+  "Enter dataset name": "Introduce el nombre de  tu dataset",
+  "Upload Audio Dataset": "Sube el audio del dataset",
   "Enter dataset path": "Introduzca la ruta del dataset",
   "Sampling Rate": "Frecuencia de muestreo",
   "RVC Version": "Versión RVC",

core.py

@@ -227,12 +227,12 @@ def run_train_script(
     g_pretrained_path=None,
     d_pretrained_path=None,
 ):
-    f0 = 1 if pitch_guidance == "True" else 0
-    latest = 1 if save_only_latest == "True" else 0
-    save_every = 1 if save_every_weights == "True" else 0
+    f0 = 1 if str(pitch_guidance) == "True" else 0
+    latest = 1 if str(save_only_latest) == "True" else 0
+    save_every = 1 if str(save_every_weights) == "True" else 0
 
-    if pretrained == "True":
-        if custom_pretrained == "False":
+    if str(pretrained) == "True":
+        if str(custom_pretrained) == "False":
             pg, pd = pretrained_selector(f0)[rvc_version][sampling_rate]
         else:
             if g_pretrained_path is None or d_pretrained_path is None:
@@ -246,25 +246,25 @@ def run_train_script(
     train_script_path = os.path.join("rvc", "train", "train.py")
     command = [
         "python",
-        train_script_path,
+        str(train_script_path),
         "-se",
         str(save_every_epoch),
         "-te",
         str(total_epoch),
         "-pg",
-        pg,
+        str(pg),
         "-pd",
-        pd,
+        str(pd),
         "-sr",
         str(sampling_rate),
         "-bs",
         str(batch_size),
         "-g",
-        gpu,
+        str(gpu),
         "-e",
         os.path.join(logs_path, str(model_name)),
         "-v",
-        rvc_version,
+        str(rvc_version),
         "-l",
         str(latest),
         "-c",

tabs/train/train.py

@@ -84,46 +84,6 @@ def refresh_datasets():
     return {"choices": sorted(get_datasets_list()), "__type__": "update"}
 
 
-# Train Temporal Fix
-def run_train(
-    model_name,
-    rvc_version,
-    save_every_epoch,
-    save_only_latest,
-    save_every_weights,
-    total_epoch,
-    sampling_rate,
-    batch_size,
-    gpu,
-    pitch_guidance,
-    pretrained,
-    custom_pretrained,
-    g_pretrained_path,
-    d_pretrained_path,
-):
-    core = os.path.join("core.py")
-    command = [
-        "python",
-        core,
-        "train",
-        str(model_name),
-        str(rvc_version),
-        str(save_every_epoch),
-        str(save_only_latest),
-        str(save_every_weights),
-        str(total_epoch),
-        str(sampling_rate),
-        str(batch_size),
-        str(gpu),
-        str(pitch_guidance),
-        str(pretrained),
-        str(custom_pretrained),
-        str(g_pretrained_path),
-        str(d_pretrained_path),
-    ]
-    subprocess.run(command)
-
-
 # Drop Model
 def save_drop_model(dropbox):
     if ".pth" not in dropbox:
@@ -170,7 +130,10 @@ def save_drop_dataset_audio(dropbox, dataset_name):
                     "The audio file has been successfully added to the dataset. Please click the preprocess button."
                 )
             )
-            return None, destination_path
+            dataset_path = os.path.dirname(destination_path)
+            relative_dataset_path = os.path.relpath(dataset_path, now_dir)
+
+            return None, relative_dataset_path
 
 
 # Train Tab
@@ -193,7 +156,7 @@ def train_tab():
                 )
                 refresh_datasets_button = gr.Button(i18n("Refresh Datasets"))
                 dataset_creator = gr.Checkbox(
-                    label=i18n("Dataset Advanced Settings"),
+                    label=i18n("Dataset Creator"),
                     value=False,
                     interactive=True,
                     visible=True,
@@ -357,7 +320,7 @@ def train_tab():
         with gr.Row():
             train_button = gr.Button(i18n("Start Training"))
             train_button.click(
-                run_train,
+                run_train_script,
                 [
                     model_name,
                     rvc_version,